swin-tiny-patch4-window7-224-mulder-v-scully-colab2
This model is a fine-tuned version of microsoft/swin-tiny-patch4-window7-224 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.5344
- Accuracy: 1.0
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
No log | 1.0 | 1 | 0.6899 | 0.5 |
No log | 2.0 | 2 | 0.6701 | 0.25 |
No log | 3.0 | 3 | 0.6309 | 0.5 |
No log | 4.0 | 4 | 0.6049 | 0.5 |
No log | 5.0 | 5 | 0.5828 | 0.5 |
No log | 6.0 | 6 | 0.5650 | 0.75 |
No log | 7.0 | 7 | 0.5486 | 0.75 |
No log | 8.0 | 8 | 0.5344 | 1.0 |
No log | 9.0 | 9 | 0.5240 | 1.0 |
0.2978 | 10.0 | 10 | 0.5149 | 1.0 |
0.2978 | 11.0 | 11 | 0.5066 | 1.0 |
0.2978 | 12.0 | 12 | 0.4980 | 1.0 |
0.2978 | 13.0 | 13 | 0.4880 | 1.0 |
0.2978 | 14.0 | 14 | 0.4699 | 1.0 |
0.2978 | 15.0 | 15 | 0.4507 | 1.0 |
0.2978 | 16.0 | 16 | 0.4310 | 1.0 |
0.2978 | 17.0 | 17 | 0.4155 | 1.0 |
0.2978 | 18.0 | 18 | 0.4054 | 1.0 |
0.2978 | 19.0 | 19 | 0.3994 | 1.0 |
0.1751 | 20.0 | 20 | 0.3970 | 1.0 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
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